MEMS: An automated multi-energy management system for smart residences using the DD-LSTM approach

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F23%3A50020665" target="_blank" >RIV/62690094:18470/23:50020665 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S2210670723004614?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2210670723004614?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.scs.2023.104850" target="_blank" >10.1016/j.scs.2023.104850</a>

Result language

angličtina

Original language name

MEMS: An automated multi-energy management system for smart residences using the DD-LSTM approach

Original language description

The increasing popularity of home automation and the rising global electricity costs have emphasized the importance of energy conservation for consumers. With smart meters, machine learning models can anticipate equipment behavior by monitoring and recording residential power use. Multi-Energy Management Systems, which allow smart grid flexibility, have garnered interest. Smart meters and smart energy gadgets in homes require autonomous multi-energy management systems. These systems should efficiently utilize real-time data to plan device consumption, reducing costs for end users. The model incorporates two Long Short-Term Memory networks, capturing short-term and long-term dependencies in energy consumption patterns. This enables the Multi-Energy Management Systems to make accurate predictions and manage energy resources in real-time. The primary objectives are to minimize reliance on the grid and maximize the utilization of renewable energy sources. The proposed Deep Dual- Long Short-Term Memory model achieves impressive accuracy rates, with scores ranging from 97% to 99% for recall, F1-score, and precision. Numerical findings demonstrate the superior performance of the proposed method compared to existing approaches, showcasing its ability to lower energy consumption and meet operational constraints. The results indicate that the proposed strategy optimizes energy use, providing cost savings and satisfying user requirements.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20701 - Environmental and geological engineering, geotechnics

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Sustainable Cities and Society

ISSN

2210-6707

e-ISSN

2210-6715

Volume of the periodical

98

Issue of the periodical within the volume

November

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

11

Pages from-to

"Article Number :104850"

UT code for WoS article

001061518500001

EID of the result in the Scopus database

2-s2.0-85169919585